Paper by Petter Törnberg and Justus Uitermark: “The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life….(More)”.
Slowed canonical progress in large fields of science
Paper by Johan S. G. Chu and James A. Evans: “The size of scientific fields may impede the rise of new ideas. Examining 1.8 billion citations among 90 million papers across 241 subjects, we find a deluge of papers does not lead to turnover of central ideas in a field, but rather to ossification of canon. Scholars in fields where many papers are published annually face difficulty getting published, read, and cited unless their work references already widely cited articles. New papers containing potentially important contributions cannot garner field-wide attention through gradual processes of diffusion. These findings suggest fundamental progress may be stymied if quantitative growth of scientific endeavors—in number of scientists, institutes, and papers—is not balanced by structures fostering disruptive scholarship and focusing attention on novel ideas…(More)”.
Solutions to Plastic Pollution: A Conceptual Framework to Tackle a Wicked Problem
Chapter by Martin Wagner: “There is a broad willingness to act on global plastic pollution as well as a plethora of available technological, governance, and societal solutions. However, this solution space has not been organized in a larger conceptual framework yet. In this essay, I propose such a framework, place the available solutions in it, and use it to explore the value-laden issues that motivate the diverse problem formulations and the preferences for certain solutions by certain actors. To set the scene, I argue that plastic pollution shares the key features of wicked problems, namely, scientific, political, and societal complexity and uncertainty as well as a diversity in the views of actors. To explore the latter, plastic pollution can be framed as a waste, resource, economic, societal, or systemic problem.
Doing so results in different and sometimes conflicting sets of preferred solutions, including improving waste management; recycling and reuse; implementing levies, taxes, and bans as well as ethical consumerism; raising awareness; and a transition to a circular economy. Deciding which of these solutions is desirable is, again, not a purely rational choice. Accordingly, the social deliberations on these solution sets can be organized across four scales of change. At the geographic and time scales, we need to clarify where and when we want to solve the plastic problem. On the scale of responsibility, we need to clarify who is accountable, has the means to make change, and carries the costs. At the magnitude scale, we need to discuss which level of change we desire on a spectrum of status quo to revolution. All these issues are inherently linked to value judgments and worldviews that must, therefore, be part of an open and inclusive debate to facilitate solving the wicked problem of plastic pollution…(More)”.
Digital Technology, Politics, and Policy-Making
Open access book by Fabrizio Gilardi: “The rise of digital technology has been the best of times, and also the worst, a roller coaster of hopes and fears: “social media have gone—in the popular imagination at least—from being a way for pro-democratic forces to fight autocrats to being a tool of outside actors who want to attack democracies” (Tucker et al., 2017, 47). The 2016 US presidential election raised fundamental questions regarding the compatibility of the internet with democracy (Persily, 2017). The divergent assessments of the promises and risks of digital technology has to do, in part, with the fact that it has become such a pervasive phenomenon. Whether digital technology is, on balance, a net benefit or harm for democratic processes and institutions depends on which specific aspects we focus on. Moreover, the assessment is not value neutral, because digital technology has become inextricably linked with our politics. As Farrell (2012, 47) argued a few years ago, “[a]s the Internet becomes politically normalized, it will be ever less appropriate to study it in isolation but ever more important to think clearly, and carefully, about its relationship to politics.” Reflecting on this issue requires going beyond the headlines, which tend to focus on the most dramatic concerns and may have a negativity bias common in news reporting in general. The shortage of hard facts in this area, linked to the singular challenges of studying the connection between digital technology and politics, exacerbates the problem.
Since it affects virtually every aspect of politic and policy-making, the nature and effects of digital technology have been studied from many different angles in increasingly fragmented literatures. For example, studies of disinformation and social media usually do not acknowledge research on the usage of artificial intelligence in public administration—for good reasons, because such is the nature of specialized academic research. Similarly, media attention tends to concentrate on the most newsworthy aspects, such as the role of Facebook in elections, without connecting them to other related phenomena. The compartmentalization of academic and public attention in this area is understandable, but it obscures the relationships that exist among the different parts. Moreover, the fact that scholarly and media attention are sometimes out of sync might lead policy-makers to focus on solutions before there is a scientific consensus on the nature and scale of the problems. For example, policy-makers may emphasize curbing “fake news” while there is still no agreement in the research community about its effects on political outcomes…(More)”.
Addressing bias in big data and AI for health care: A call for open science
Paper by Natalia Norori et al: “Bias in the medical field can be dissected along with three directions: data-driven, algorithmic, and human. Bias in AI algorithms for health care can have catastrophic consequences by propagating deeply rooted societal biases. This can result in misdiagnosing certain patient groups, like gender and ethnic minorities, that have a history of being underrepresented in existing datasets, further amplifying inequalities.
Open science practices can assist in moving toward fairness in AI for health care. These include (1) participant-centered development of AI algorithms and participatory science; (2) responsible data sharing and inclusive data standards to support interoperability; and (3) code sharing, including sharing of AI algorithms that can synthesize underrepresented data to address bias. Future research needs to focus on developing standards for AI in health care that enable transparency and data sharing, while at the same time preserving patients’ privacy….(More)”.
The Survival Nexus: Science, Technology, and World Affairs
Book by Charles Weiss: “Technology and science can enable us to create a richer, healthier, sustainable, and equitable world, but they can also lead to global disaster. After all, human technical, political, economic, business, and ethical decisions determine the impact of scientific discoveries and technological innovations…
In this book, Charles Weiss explores the intertwining of science, technology, and world affairs that affects everything from climate change and global health to cybersecurity, biotechnology, and geoengineering. Compact and readable, the book ties together ideas and experiences arising from a broad range of diverse issues, ranging from the structure of the energy economy to the future of work and the freedom of the internet.
The Survival Nexus highlights opportunities to mobilize science and technology for a better world through technological innovations that address global health, poverty, and hunger. It alerts the reader to the Earth-in-the balance risks stemming from the decline in the international cooperation that once kept the dangers of pandemics, climate change, and nuclear war in check. It warns of the challenge to democracies from the multi-faceted global information and cyber-wars being waged by authoritarian powers. Central to the global problems it explores are questions of basic ethics: how much are people willing to respect scientific facts, to act today to forestall long-run dangers, and to ensure equitable sharing of the benefits, costs, and risks arising from advances in science and technology.
Weiss clearly explains the technical principles underlying these issues, showcasing why scientists, policy makers, and citizens everywhere need to understand how the mix of science and technology with politics, economics, business, ethics, law, communications, psychology, and culture will shape our future. This important nexus underpins issues critical to human survival that are overlooked in the broader context of world affairs…(More)”.
Impact Evidence and Beyond: Using Evidence to Drive Adoption of Humanitarian Innovations
Learning paper by DevLearn: “…provides guidance to humanitarian innovators on how to use evidence to enable and drive adoption of innovation.
Innovation literature and practice show time and time again that it is difficult to scale innovations. Even when an innovation is demonstrably impactful, better than the existing solution and good value for money, it does not automatically get adopted or used in mainstream humanitarian programming.
Why do evidence-based innovations face difficulties in scaling and how can innovators best position their innovation to scale?
This learning paper is for innovators who want to effectively use evidence to support and enable their journey to scale. It explores the underlying social, organisational and behavioural factors that stifle uptake of innovations.
It also provides guidance on how to use, prioritise and communicate evidence to overcome these barriers. The paper aims to help innovators generate and present their evidence in more tailored and nuanced ways to improve adoption and scaling of their innovations….(More)”.
Data governance: Enhancing access to and sharing of data
OECD Recommendation: “Access to and sharing of data are increasingly critical for fostering data-driven scientific discovery and innovations across the private and public sectors globally and will play a role in solving societal challenges, including fighting COVID-19 and achieving the Sustainable Development Goals (SDGs). But restrictions to data access, sometimes compounded by a reluctance to share, and a growing awareness of the risks that come with data access and sharing, means economies and societies are not harnessing the full potential of data.
Adopted in October 2021, the OECD Recommendation on Enhancing Access to and Sharing of Data (EASD) is the first internationally agreed upon set of principles and policy guidance on how governments can maximise the cross-sectoral benefits of all types of data – personal, non-personal, open, proprietary, public and private – while protecting the rights of individuals and organisations.
The Recommendation intends to help governments develop coherent data governance policies and frameworks to unlock the potential benefits of data across and within sectors, countries, organisations, and communities. It aims to reinforce trust across the data ecosystem, stimulate investment in data and incentivise data access and sharing, and foster effective and responsible data access, sharing, and use across sectors and jurisdictions.
The Recommendation is a key deliverable of phase 3 of the OECD’s Going Digital project, focused on data governance for frowth and well-being. It was developed by three OECD Committees (Digital Economy Policy, Scientific and Technological Policy, and Public Governance) and acts as a common reference for existing and new OECD legal instruments related to data in areas such as research, health and digital government. It will provide a foundation stone for ongoing OECD work to help countries unlock the potential of data in the digital era….(More)”.
A History of the Data-Tracked User
Essay by Tanya Kant: “Who among us hasn’t blindly accepted a cookie notice or an inscrutable privacy policy, or been stalked by a creepy “personalized” ad? Tracking and profiling are now commonplace fixtures of the digital everyday. This stands even if you use tracker blockers, which have been likened to “using an umbrella in a hurricane.”
In most instances, data tracking is conducted in the name of offering “personalized experiences” to web users: individually targeted marketing, tailored newsfeeds, recommended products and content. To offer such experiences, platforms such as Facebook and Google use a dizzyingly extensive list of categories to track and profile people: gender, age, ethnicity, lifestyle and consumption preferences, language, voice recordings, facial recognition, location, political leanings, music and film taste, income, credit status, employment status, home ownership status, marital status — the list goes on….
As I explore in this case study, and as part of my work on algorithmic identity, data tracking does not just match the “right” people with the “right” products and services — it can discriminate, govern, and regulate web users in ways that demand close attention to the social and ethical implications of targeting.
It is not an overstatement to propose that data tracking underpins the online economy as we know it.
Commercial platform providers frame data tracking as inevitable: Data in exchange for a (personalized) service is presented as the best, and often the only, option for platform users. Yet this has not always been the case: In the mid-to-late 1990s, when the web was still in its infancy, “cyberspace” was largely celebrated as public, non-tracked space which afforded users freedom of anonymity. How then did the individual tracking of users come to dominate the web as a market practice?
The following timeline outlines a partial history of the data-tracked user. It centers largely on developments that have affected European (and to a lesser extent U.S.) web users. This timeline includes developments in commercial targeting in the EU and U.S. rather than global developments in algorithmic policing, spatial infrastructures, medicine, and education, all of which are related but deserve their own timelines. This brief history fits into ongoing conversations around algorithmic targeting by reminding us that being tracked and targeted emerges from a historically specific set of developments. Increased legal scrutiny of targeting means that individual targeting as we know it may soon change dramatically — though while the assumption that profiling web users equates to more profit, it’s more than likely that data tracking will persist in some form.
1940s. “Identity scoring” emerges: the categorization of individuals to calculate the benefits or risks of lending credit to certain groups of people….(More)”.
Mobile Big Data in the fight against COVID-19
Editorial to Special Collection of Data&Policy by Richard Benjamins, Jeanine Vos, and Stefaan Verhulst: “Almost two years into the COVID-19 pandemic, parts of the world feel like they may slowly be getting back to (a new) normal. Nevertheless, we know that the damage is still unfolding, and that much of the developing world Southeast Asia and Africa in particular — remain in a state of crisis. Given the global nature of this disease and the potential for mutant versions to develop and spread, a crisis anywhere is cause for concern everywhere. The world remains very much in the grip of this public health crisis.
From the beginning, there has been hope that data and technology could offer solutions to help inform governments’ response strategy and decision-making. Many of the expectations have been focused on mobile data analytics, and in particular the possibility of mobile network operators creating mobility insights and decision-making tools generated from anonymized and aggregated telco data. This hoped-for capability results from a growing group of mobile network operators investing in systems and capabilities to develop such decision-support products and services for public and private sector customers. The value of having such tools has been demonstrated in addressing different global challenges, ranging from the possibilities offered by models to better understand the spread of Zika in Brazil to interactive dashboards that aided emergency services during earthquakes and floods in Japan. Yet despite these experiences, many governments across the world still have limited awareness, capabilities, budgets and resources to leverage such tools in their efforts to limit the spread of COVID-19 using non-pharmaceutical interventions (NPI).
This special collection of papers we launched in Data & Policy examines both the potential of mobile data, as well as the challenges faced in delivering these tools to inform government decision-making. To date, the collection
Consisting of 11 papers from 71 researchers and experts from academia, industry, and government, the articles cover a wide range of geographies, including Argentina, Austria, Belgium, Brazil, Ecuador, Estonia, Europe (as a whole), France, Gambia, Germany, Ghana, Italy, Malawi, Nigeria, Nordics, and Spain. Responding to our call for case studies to illustrate the opportunities (and challenges) offered by mobile big data in the fight against COVID-19, the authors of these papers describe a number of examples of how mobile and mobile-related data have been used to address the medical, economic, socio-cultural and political aspects of the pandemic….(More)”.